Hi, Mary. Hi. I give you. So you should be able to start your camera. Same for you Kathy you should know it is closed. Curtis. Perfect. I'm going to make sure everybody can get your cameras on real quick. I clicked on it and not seeing anything. If you go to your video. Your video settings, are you able to select your intern integrated camera. That's what it says it's on integrated webcam. Do you have the little slider over your camera. Do you want to try to leave and come back real quick. And then while she's doing that do you guys want to pull up your slides we can make sure you can share. Yeah. All right, everyone. Welcome. We are joined here by Kyle sports Curtis maze, and we are going to be joined by Mary Lindahl as well so she's got a camera issue, but with that, this session is called AI adoption challenges the status. Whoa. Are you ready for improved performance. Welcome back, Mary, I'm getting you the right so hopefully your camera will work this time. So in this session we're going to be exploring the challenges and opportunities of AI adoption in healthcare. And, as I said, we're joined by Kyle sports who's president of AI health. Curtis maze who's the vice president of business development and strategy AI health and Mary Lindahl who's the coding manager for revo health, and they're going to be sharing their expertise on how to strategically implement AI for improved performance. So without further ado, I'm going to pass it on to Kyle. Thank you, Jessica and AoE and, you know, kudos to the presenters before us a lot of really fantastic content that kind of leads into, you know, what is AI, what are the different components to the regulatory concerns the practical application, and some of the So joining me today is obviously Maryland doll from revo health in Twin Cities orthopedics and Curtis maze, who previously served as the CEO of steamboat orthopedics and our, our goal today is is pretty simple. You know, we want to make sure that you all understand some of the business problems I think they've already been identified across the board and I think potato gave us some good examples. There's a lot of paralysis and it can be overwhelming. Where do you start, where do you go. What's the best use of the time that you probably don't have. And then what do you need to do to go to the C suite and get by and and Mary will share with you that you have to have executive buy in. for any type of AI deployment to be successful, largely because of the transformational nature of the cultural impact the financial impact. The expected outcomes that may need to be level set in terms of timing which leads into, you know, what ROI metrics, should we be tracking both tangible and non tangible related to, you know, the consumers and end users being able to use it and feel that And then we do feel as though, you know, we, we don't have, you know, all of the, all of the answers around where AI is going because it's, you know, ever evolving even as we speak. And there's a lot of genies left in the bottle. But where do we think the puck is headed. And then where and how can you, you know, engage your organization for some strategies. You know, what's interesting is my father who's 78 years old, I tried to explain to him what artificial intelligence is. And I said, well, dad, it's, it's like a gold rush and he goes, well, I don't get it. He goes, is it the same as the dot com bubble. Are we repeating that hype cycle where there's innovation, enthusiasm, transformation, the end of the world is coming, but also the speculative nature of its outcomes and obviously we're on, on the internet right now and we continue to, to drive forward but but in all seriousness, I mean, it's almost uncool these days to not be talking about AI, it's on ads and billboards and all over the place, but it's real. And I think the hype is legit. And obviously as as either clinicians, administrators, executives, and even end users, it's clear that we do need a helpful coworker and there was a lot of sentiments around the fact that AI is not going to take your job but the goal is to have that gentle nudge at the point of care or to make that expert coder more efficient. But across the board, we're seeing, you know, this dominate the headlines and you, and you do see that. What's interesting as well is over the last 12 to 18 months as we've worked with many large orthopedic practices and other specialty practices across the board, their executives as well as private equity and venture capitalists are actually validating that there is the shift now from academic curiosity of AI to the practical application. Like there's no, no longer can we just sit here in this hamster wheel, trying to figure out what to do. You've got to do it. It's not a nice to have, it's a gotta have. And so, as we think about, as we think about the adoption, the adoption is here and it's real. And we've got to start thinking about where and how we move, how we move you and the organization forward. So we'll share some, some ideas and tactics here. We have a quick poll question. Did you want to bring that up? Should be launching now. Oh, perfect. It's always interesting to see where organizations are looking to deploy. A lot of good ideas, a lot of good topics. Curious where everyone is focused in their efforts at this point. Clinical documentation seems to be taking the lead. Coding, documentation. Coding, documentation. Well, that makes total sense. I mean, if you look at, you know, where the market is headed, and we've only got, you know, 22 people answering it, it wouldn't surprise me or anyone that, you know, clinical documentation is leading the pack. It continues to be the bane of existence for a lot of providers with physician burnout at all time highs. And medical coding, which continues to be the Achilles heel, whether it's from staffing and labor shortages to reimbursement challenges to even what the previous presenter shared about the payers denying for whatever reason they so feel fit that day based on the algorithms that they've deployed. So what's interesting is this kind of lines up to what the market is saying as well. So Medscape produces a report. And this is interesting because it really is, where do we start and where do we go? And I think what we just saw in the recent poll is that a lot of organizations are looking at whether it falls in the EHR bucket or the ambient listening bucket, administrative tasks and such continue to lead the pack. And I think, you know, there's this goal of kind of first do no harm. I mean, obviously, we would like to get to a point where we're able to leverage AI in a larger kind of broader scale for clinical outcomes and clinical diagnosis. But I still think we're still some time away from that. I mean, physicians are obviously more receptive to its use, and I have some stats I'll share with you here shortly. But what's interesting in another study is about 60 to 65 percent of consumers of health care are very skeptical of AI and its applicable use as it relates to care. And so where and how can we get the patients more engaged and comfortable? How do we get the clinicians more engaged and comfortable? And I think that's going to take time. So, you know, I anticipate that over the next year or two, you're going to see a bit of a shift here. You're going to see some aggregation of these capabilities. And so, you know, what if you had an ambient documentation solution paired with a robust autonomous coding solution? What if you had a robust prior authorization capability with, you know, being able to append that, Mary, to the note when you're dealing with denials, right? And so there's a lot of, I think, overlap and consolidation that we'll see. But I think the key here is, you know, a lot of those have high percentages, 79 percent, 78 percent. Where do you start? You can't do it all. And so I think this goes back to some of the earlier conversations and where we kind of lead in with our kind of ex-consultant hats to say, you really need to look inside the four walls of your practice and determine what is going to give you the biggest bang. There's no way you'll be able to deploy these all successfully and feel confident in its outcomes. So I think taking a crawl, walk, run approach is going to be really important. One of the other areas that I think is interesting, and someone alluded to it on a previous call, is around the area of leveraging chat GPT just to get a head start. Earlier this year, I was presenting at the Illinois chapter of the Healthcare Financial Management Association, and there was about 200 people in the room. And I asked, who in this room is deploying AI? And one poor lady raised her hand and said, me. And I said, how are you using AI? And she said, well, I used it to start to write an appeal letter. And I said, that's a start. And I said, did you use it? She said, yes. And I said, is it your template going forward? She said, yes. And these were major health systems and large physician groups that 12 to 18 months ago weren't looking to adopt. If I was to go back in that room today, I bet you a large portion, I would hope half of them are starting to leverage some type of AI capabilities. So, where do we start? Then you have to pick the vendor, right? So, there's a multi, multi-billion dollar ecosystem around AI, generative AI, and the AI landscape. Where do you start? And I will tell you that this is probably 18 months old. So, as we look at this, there are some that are gone. There are some that have been acquired. There are some that are in a consolidation phase, or there's a bunch of new entrants. And so, as a consumer of AI solutions and trying to figure it out, it's going to be really key to identify the use case, pick a partner or two to go through kind of a pilot, if you may, and determine what is the best path forward. As it relates to pilots, we all have done them. They can be exhausting, time consuming, and don't really have a level of KPIs and kind of mutual success. If you're going to be successful in deploying any of these AI solutions, you do need to make sure that you're dedicated, focused, and have funding and an end goal in mind, or else you'll just be on this continuous treadmill with unlikely outcomes that won't be likely taken well in the boardroom by your physicians or by your leadership team. So, as you think about vetting the landscape, it's going to be important to really dwell into who these vendors are and what they do, what the type of AI do they use. I mean, we've gone through a couple educational sessions in the last two hours on all types of AI use cases. But at the end of the day, I think it's important for you to go through a true vendor analysis and selection on what it is that you're trying to solve, and then buckle up and get ready to deploy resources internally as well as capital to make it tick. This is not a set it and forget it. And what's interesting in some of the challenges that I think you'll face is that just because you deploy an AI solution doesn't mean it's going to have immediate return. And we'll talk a little bit about that kind of ongoing carry and feed when we get to Mary's part of the presentation. So, I'll just kind of chime in here, and Mary's going to take a stab at these as well, but you have to keep an open mind. And the fear factor that the robots are taking over the world is real, but it needs to be suppressed, it needs to be understood, and people are obviously mindful of their jobs. And so, Mary, you know, you've had experience with this, any additional insights that you would share with the group would be valuable here. Yeah, I think that was a major fear with coders, and I sensed it right away. So, it's keeping them involved in knowing what's happening and constant reminders about this isn't going to take your job, it's to help. We can't find enough qualified people, and you're overwhelmed, you're working overtime, we're trying to pay incentives. I know everybody doesn't want to work as many hours as we'd love for them to work. So, this is a helper, not a taker over. So, I've had to reiterate that over and over and over again. And be mindful that they don't know the full scope, and so they do get nervous. It's always about me. We all know that. It's always about me as a person and my job. So, how do I reassure them? So, it's just a constant reminder and a reassurance to them. And they're seeing it as it's implemented. Oh, okay. Yeah, it's helping, it's not taking over, and it's not doing everything, and it's never going to do everything. Yeah, Thank you, Mary. I mean, you're living and breathing every day. It is a campaign that starts from the top and needs to be an ongoing exercise, particularly if you deploy new models or move into new specialties, people can have a different level of concern across the board. I think we've hammered the research and education piece around all of these acronyms. You've got to really know what you're getting yourself into. And, you know, I think people are very quick to say AI. We deploy AI. It's all over the place. But I think you need to get to the second, third, fourth, and maybe fifth level of detail there, because AI is not necessarily a rules engine. Rules engines have been around for a while. And so how are you using rules engines and robotic process automation and other kind of key functionality to be able to deploy? That's kind of up to you. The executive sponsorship, I can't reinforce enough. I mean, every organization that we work today, their CEO is actively engaged. And, you know, Curtis will talk a little bit here on the next slide about, you know, through the lens of a CEO, when you do deploy this, here are some of the key considerations, particularly if you're in a physician owned practice, how are you going to deploy and use these funds? We don't have a bolus of cash that's kind of in our reserve that should go towards our monthly or quarterly bonus, what have you. But you do need to have leaders involved to feel comfortable, allocate funds for innovation. And some organizations don't have the appetite to do that. That is perfectly fine. Not every organization is mature enough or ready to deploy AI. But if you are willing to do it, funding and looking at it through the lens of experimentation is going to be critical, because it may not work or work as fast, or you may have picked the wrong partner. But the business case or the use case is still something that is mission critical for you to solve for. And then, you know, continuous improvement is certainly something again, in working with Mary and the Revo and Twin Cities team, we've been at this for well over a year now. And it's a constant iterative process where that collaboration between vendor and client partner, particularly in the early deployment of AI is mission critical. And a lot of our understanding and knowledge of the workflows and the nuances of the business comes from Mary and her team, a lot of the innovation and the contemporary technology deployment comes from us. And when you pair those together, you're starting to see a pretty unique and symbiotic relationship between vendor and client versus an adversarial relationship. Well, it doesn't work, it's too many clicks, what's going on, there has to be that kind of joint effort. And in any scenario, we have this kind of big conceptual mindset. I remember meeting with Mary and team, the first couple of weeks is can we do this? Can we do this? Can we do this? Can we do this? And we still are in a bit of that, which is great, because it is forcing us to be on our toes, but also a constant piece of innovation. I'll pause and see if there's any questions before I pass it over to Curtis. Any Curtis or any in the chat? I don't see anything in the chat yet, but I'll definitely prompt you if something comes up after the Q&A. Got it. Thank you. Yeah, thank you. Curtis? Thanks, Kyle, Mary. You know, being a leader of orthopedic practices a few times, for me, revenue cycle performance was always key. Make sure cash flow, make sure we get tangible revenue cycle performance. And to that end, obviously, the team that's leading that, driving that is essential. So, as Mary talked about relative to finding talented coders, making sure you don't have a shortage, you're not paying for excessive overtime, those type of things. All those are critical elements. And from our perspective also, as trying to challenge the status quo, what is it that can happen? What can you do tangibly to make a difference? What's that value? So, you can see on the screen here, relative to those, the very first one, the value delivered. As a CEO, you're asking that question all the time. We're going to deploy new technology. What does that look like? What's a tangible savings realized, increased volume, improved financial benefit relative to AR days, cash flow, other things that might cause those aspects? And you're going to hear quite a bit from Mary and Kyle, much more about the actual impact of that, that happened for Mary's organization relative to that, that benefit, that how significant it was for them and changed dramatically sort of day-to-day, what they're looking at and seeing. You know, I think also, as you, that change management, as Kyle talked about, is significant. Understanding that things have to change, they have to improve, they have to evolve into that component. And what does that look like? And what does that mean? And being ready for that change is essential. And what's important to that. And to that end, as Kyle also mentioned, is that leadership, embracing that and being involved in that, and not just hoping to send it over the fence and hoping the revenue cycle team can handle it, manage it, those types of things. Leadership is critical to help navigate the elements that go on there. And then certainly that continuous improvement and adaptation. What do we keep doing? How do we keep pushing? What do we work towards to continue to improve? Because once, as we know with EarthBeak surgeons, once you make one sizable leap forward, it won't be long before they're asking for that next leap forward. So continue to find those ways to work and gain that momentum. And it's certainly hard. I mean, you know, Curtis, you're a brave soul. I mean, challenging the status quo is not always well-received or something that an individual wants to embrace. And so, again, this could be one of those, you know, potential job-impacting decisions. But I think well thought out, well-delivered with the right partner could have an opposite effect that actually could force you to now have to do more. Like you said, what's the next project, Curtis? What's the next project, Mary? Where do we go from here? And so we're going to pass it off to Mary now. I think this is a good you know, we're going to do a little case study here, but I think this is a prime example of what we just discussed and was discussed earlier today. Identification of a need, putting together kind of a business case, finding the right partner, you know, creating the right funding mechanisms, educating their team on the why, and then this continuous improvement and deployment exercise within a very large orthopedic practice and revenue cycle management company. So without further ado, I'll hand it over to Mary to give you a little background on REVO and Twin Cities as it relates to the scale, because it's big. And then we'll walk you through a little bit of the approach and timeline that we took. Thanks, Kyle. So just to give you a little perspective, and when Kyle says big, yeah, when I look at the numbers, I'm like, yeah, it's pretty big. So REVO is actually a management service organization. So we have multiple clients, multi-specialties. So we're 850 plus providers, including ortho and other specialties, PT, women's health, some other divisions. I'm looking at my numbers, 19 private practice physician groups, 50 plus unique taxonomies, and we generate about 60,000 surgical cases, ortho, just ortho surgical cases a year, and about 1.4 million total patient encounters. So we're a little on the large side. So to say when I walked into the organization three years ago, it was a little intimidating. I had been doing this a long time, but it was still a little intimidating. Currently, I have about 70 coders, and I kind of walked into a time warp in that the TCO providers, none of them picked their codes, and all my coders abstracted. So I'm trying to get coders that even know the word abstracting anymore after working on systems like Epic. They don't even know what that means. So having them read the documentation and come up with everything can be very intimidating. So not only am I up against finding qualified coders, but finding qualified coders that know actually how to abstract and not just verify information and verify what the provider has picked. We're talking about actually coding diagnosis codes and coding CPG codes for everything. So selfishly, I said, this isn't going to work long-term. So we started talking, my VP and I, okay, what are some solutions? Well, I'd heard about computer-assisted coding. Well, you know, it's okay, but I needed something that was really going to have an impact. So we started looking, my VP in particular started looking for different products, and she came across AI Health, and it just seemed like the right partnership. They were willing to work with us and not tell us, well, this is how we designed it. They wanted our input and still continue to want our input, which is phenomenal. I think that's a big, like Kyle said, that's a big part of this relationship. It is a relationship. It's not, we're buying your product and we're going to use it as is. It's molding the product and getting it so it works for both sides. And we've done that in the slide that Kyle has up. It may seem like it's a long time, but it's not, and it goes very quickly. So we started with surgical coding, and I can tell you it was able to be sold to executive leadership by saying, okay, when we bring on 10 or 15 physicians in September, when they finish their programs, I'm not going to have to hire five more coders. That's enough to say, okay, and we can cut down on overtime and we're not going to have to offer incentives to get coders to come work for us. So those are all sales techniques and tactics that you can use for executive leadership. And then when they start to see the impact, so surgical coding, we were probably in the five to seven day range and sometimes longer out from when coding received the op report. And now my coders code today's, what we get today, what's sent to us today, which may have been surgeries done yesterday and yesterday's cases. So we're a day, two days out maximum. So when you tell them, oh, we're going to bill out all the surgeries that were done yesterday, the eyes light up with executive leadership. They're going to, that's going to sell it. And they're going to see a quicker return on their investment in their money. So working with AI health, and now we're moving into E&M coding, which hopefully we will be turning on next week. It's timely that this conversation's coming up because we're looking at that. So how can I save staff and not burn them out? That's another problem and not have to hire as many people coming in as we're hiring 68 physicians starting soon. So in the month of September, and I have no intention of actually bringing in additional coding staff, maybe some contracted staff to fill the gap while we're ramping up on the E&M side, but it's been very productive. We definitely have a return on the, on investment and it's an easy sell to executive leadership coders as they get into it and see it. They sell it for us too. They're excited. I have some coders that were still working in our old system. And every day I hear from them, it's hard working in here. Can't we work in AI health? Because it's so much quicker and so much easier and more intuitive. So the coders aren't afraid anymore. They still need the reassurance. It's never going to take your job away, but it's going to be that helpful coworker that Kyle's been referencing. Well, thank you, Mary. That's great. I mean, I think again, big picture is you got to level set expectation. And lastly, I think if anyone says that they can autonomously code a hundred percent of all your E&Ms and your surgical cases, I would call a bluff. In the world of soccer, I would call, I would give a straight red card, but just some closing thoughts. I know we're, we're wrapping up. I mean, we've identified both on your poll and national polls across the board, we should look to deploy AI in administrative functions. First, do no harm. There's a lot of use cases. Let's go hard and fast to that. Mary's example gives a clear ROI in case study within that middle revenue cycle, specifically coding. Let's look at how we can continue to encourage physicians to adopt AI as well as figuring out ways to ease in patients of varying degrees of age and knowledge in the space. And, you know, obviously prepare for, you know, continued increased scrutiny per our legal advice that we got earlier today. And so again, we appreciate the opportunity to present. Hopefully this was helpful, you know, use these tactics, leverage, you know, Curtis and Mary as, as your helpful coworker. If you're looking to put together use cases, but thanks again for the time. And we appreciate you having us today. Thank you so much. Really quick. I think this is a question for Mary. Have you been audited since you've had this in place? We are audited all the time by payers. So, you know, they're always asking for records. So yeah, I mean, it's happening all the time with getting requests from payers and we provide the records and always pass with flying colors. So no red flags with that. Obviously internally, you need to be looking at yourself and doing internal audits in general, which we do anyway. So we don't want things going out the door inappropriately. And therefore we're going to cover our bases internally before somebody externally comes knocking on our door. Awesome. All right. Thank you all so much for this. We have another five minute break scheduled. So everyone can take another quick break to either check email or run to the restroom, whatever you need to do. We will get started next at 328. Thank you. And see you all in a few minutes. Thank you. Thank you, Mary. Thank you, Curtis.

AI adoption

healthcare

coding practices

surgical coding

E&M coding

executive buy-in

return on investment